The ongoing Ebola epidemic in West Africa (primarily Guinea, Liberia, and Sierra Leone) provides a valuable case study in the importance of diagnostics for febrile illness. Prior to widespread knowledge of the Ebola outbreak, a patient presenting with fever and chills might be diagnosed with malaria, purely on the basis of symptoms with no follow-up tests. If this diagnosis is incorrect, the patient does not get the appropriate therapy, and if the patient in fact has Ebola or other contagious virus, this can lead to spread of the virus which complicates infection control. We propose to develop a simple, inexpensive, portable diagnostic device to detect a panel of viruses that may be endemic in West Africa: Ebola virus, Lassa virus, Yellow Fever virus, Chikungunya virus, Dengue virus, and West Nile virus; as well as Plasmodium falciparum (the most serious cause of human malaria). The device will be simple enough to operate at a simple field clinic, triage center, airport, or other resource-poor location, utilizing a novel assay cartridge with stabilized reagents to eliminate reliance on cold chain. Supporting hardware will be battery- or solar-powered, and uses a smart phone camera for assay detection, data analysis and reporting. The assay is based on isothermal amplification of pathogen RNA, using a novel chemistry that allows single-step, closed tube multiplex detection of targets using fluorescent probes and quenchers. The proposed work is a collaborative effort between the Biotechnology and Bioengineering group at Sandia National Laboratories, and the Institute for Human Health and Immunity at the University of Texas Medical Branch. The proposed work begins with proof-of-concept (R21) phase, during which the assays and prototype hardware are tested and verified for sensitivity and specificity for model strains of pathogens. If successful, the work proceeds to a development (R33) phase, during which the prototype assay and hardware are refined, and validated by testing with clinical specimens and blood from animal model infections.